tuesdata <- tidytuesdayR::tt_load('2021-08-31')
tuesdata <- tidytuesdayR::tt_load(2021, week = 36)
bird_baths <- tuesdata$bird_baths
library(shiny)
library(plotly)
survey_year <- unique(bird_baths$survey_year)
urural <- unique(bird_baths$urban_rural)
bioregions <- unique(bird_baths$bioregions)
print(survey_year)
[1] 2014 2015 NA
print(urural)
[1] "Urban" "Rural" NA
print(bioregions)
[1] "South Eastern Queensland" "NSW North Coast" "Sydney Basin" "South Eastern Highlands"
[5] "South East Coastal Plain" "Brigalow Belt South" "NSW South Western Slopes" "Victorian Volcanic Plain"
[9] "Victorian Midlands" "Flinders Lofty Block" NA
urbanrural <- df %>%
group_by(survey_year, urban_rural) %>%
count(sort = TRUE)
y <- c('giraffes', 'orangutans', 'monkeys')
SF_Zoo <- c(20, 14, 23)
LA_Zoo <- c(12, 18, 29)
data <- data.frame(y, SF_Zoo, LA_Zoo)
fig <- plot_ly(data, x = ~SF_Zoo, y = ~y, type = 'bar', orientation = 'h', name = 'SF Zoo',
marker = list(color = 'rgba(246, 78, 139, 0.6)',
line = list(color = 'rgba(246, 78, 139, 1.0)',
width = 3)))
fig <- fig %>% add_trace(x = ~LA_Zoo, name = 'LA Zoo',
marker = list(color = 'rgba(58, 71, 80, 0.6)',
line = list(color = 'rgba(58, 71, 80, 1.0)',
width = 3)))
fig <- fig %>% layout(barmode = 'stack',
xaxis = list(title = ""),
yaxis = list(title =""))
fig
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